Ranking methods for many-objective optimization M Garza-Fabre, G Pulido, C Coello MICAI 2009: Advances in Artificial Intelligence, 633-645, 2009 | 158 | 2009 |
An improved and more scalable evolutionary approach to multiobjective clustering M Garza-Fabre, J Handl, J Knowles IEEE Transactions on Evolutionary Computation 22 (4), 515-535, 2017 | 56 | 2017 |
Two novel approaches for many-objective optimization M Garza-Fabre, G Toscano-Pulido, CAC Coello IEEE Congress on Evolutionary Computation, 1-8, 2010 | 48 | 2010 |
Alternative fitness assignment methods for many-objective optimization problems MG Fabre, GT Pulido, CAC Coello Artificial Evolution: 9th International Conference, Evolution Artificielle …, 2010 | 45* | 2010 |
Generating, maintaining, and exploiting diversity in a memetic algorithm for protein structure prediction M Garza-Fabre, SM Kandathil, J Handl, J Knowles, SC Lovell Evolutionary computation 24 (4), 577-607, 2016 | 42 | 2016 |
Effective ranking+ speciation= many-objective optimization M Garza-Fabre, G Toscano-Pulido, CAC Coello, E Rodriguez-Tello 2011 IEEE Congress of Evolutionary Computation (CEC), 2115-2122, 2011 | 33 | 2011 |
Constraint-handling through multi-objective optimization: The hydrophobic-polar model for protein structure prediction M Garza-Fabre, E Rodriguez-Tello, G Toscano-Pulido Computers & Operations Research 53, 128-153, 2015 | 28 | 2015 |
Multi-objectivization, fitness landscape transformation and search performance: A case of study on the hp model for protein structure prediction M Garza-Fabre, G Toscano-Pulido, E Rodriguez-Tello European Journal of Operational Research 243 (2), 405-422, 2015 | 27 | 2015 |
Locality-based multiobjectivization for the HP model of protein structure prediction M Garza-Fabre, G Toscano-Pulido, E Rodriguez-Tello Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012 | 25 | 2012 |
Comparative analysis of different evaluation functions for protein structure prediction under the HP model M Garza-Fabre, E Rodriguez-Tello, G Toscano-Pulido Journal of Computer Science and Technology 28 (5), 868-889, 2013 | 23 | 2013 |
Improved fragment-based protein structure prediction by redesign of search heuristics SM Kandathil, M Garza-Fabre, J Handl, SC Lovell Scientific Reports 8 (1), 13694, 2018 | 19 | 2018 |
An evolutionary many-objective approach to multiview clustering using feature and relational data A José-García, J Handl, W Gómez-Flores, M Garza-Fabre Applied Soft Computing 108, 107425, 2021 | 16 | 2021 |
Multiobjectivizing the HP model for protein structure prediction M Garza-Fabre, E Rodriguez-Tello, G Toscano-Pulido Evolutionary Computation in Combinatorial Optimization: 12th European …, 2012 | 16 | 2012 |
A new reduced-length genetic representation for evolutionary multiobjective clustering M Garza-Fabre, J Handl, J Knowles Evolutionary Multi-Criterion Optimization: 9th International Conference, EMO …, 2017 | 11 | 2017 |
Handling constraints in the HP model for protein structure prediction by multiobjective optimization M Garza-Fabre, G Toscano-Pulido, E Rodriguez-Tello 2013 IEEE Congress on Evolutionary Computation, 2728-2735, 2013 | 11 | 2013 |
Joint route selection and split level management for 5G C-RAN CC Erazo-Agredo, M Garza-Fabre, RA Calvo, L Diez, J Serrat, ... IEEE Transactions on Network and Service Management 18 (4), 4616-4638, 2021 | 10 | 2021 |
An improved multiobjectivization strategy for hp model-based protein structure prediction M Garza-Fabre, E Rodriguez-Tello, G Toscano-Pulido International Conference on Parallel Problem Solving from Nature, 82-92, 2012 | 9 | 2012 |
Comparing alternative energy functions for the HP model of protein structure prediction M Garza-Fabre, E Rodriguez-Tello, G Toscano-Pulido 2011 IEEE Congress of Evolutionary Computation (CEC), 2307-2314, 2011 | 7 | 2011 |
Many-view clustering: An illustration using multiple dissimilarity measures A José-García, J Handl, W Gómez-Flores, M Garza-Fabre Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2019 | 5 | 2019 |
Optimización de problemas con más de tres objetivos mediante algoritmos evolutivos MG Fabre | 5* | |